(1) Field of the Invention
The present invention relates to a block noise detecting method and apparatus, and a block noise reducing method and apparatus. More specifically, the present invention relates to a method and apparatus for detecting a size, position and intensity of a block noise, and a method and apparatus for reducing the block noise on the basis of a result of the detection.
(2) Description of Related Art
Beginning of spread of digital broadcasting, DVD players, disk recorders and so forth to which the digital image compression coding technique is applied gives us more opportunity to view compression-coded pictures. As this, compression-coded pictures are getting closer to us.
MPEG-2, which is International Standard for image compression used in digital broadcasting, disk recorders and so forth, realizes image compression in the domain of time with motion compensation which refers an analogous portion between picture frames. Therefore, the difficulty of the compression changes according to the contents of the picture. When the difficulty of image compression is great because there is little analogous portion between image frames (hereinafter, referred to simply “frame”), the image data is encoded at high compression ratio. This causes loss of high frequency components of the picture, which causes loss of the continuity of pixel values in the vicinity of the border of blocks, leading to a rectangular noise, that is, a block noise, on the restored picture.
As known techniques for detecting and reducing such block noises, there are techniques proposed in the following Patent Documents 1 to 4.
(1) The technique disclosed in Patent Document 1 is aimed to accurately detect a block noise even when a decoder does not output a signal indicating the boundary of pixel blocks. For this purpose, an input video signal is differentiated to detect a solitary differentiation point (impulse-shaped pulse) in the differentiated signal, a result of the detection is integrated in cycles of pixel blocks by an integrating circuit, information on the solitary differentiation points generated in cycles of the pixel blocks is accumulated, and presence or absence of a block noise is determined in each frame on the basis of the output of the integrating circuit. Accordingly, even when the border of the pixel blocks is vague, it is possible to accurately determine presence or absence of a block noise. Additionally, by performing the integrating process in the horizontal and the vertical directions, it becomes possible to appropriately detect an impulse-shaped pulse correlating in the horizontal and the vertical directions, which has generated due to a block noise. This allows accurate determination on presence or absence of a block noise.
The technique disclosed in Patent Document 2 is aimed to provide a block noise reducing apparatus having a simple constitution. For this purpose, an input video signal is differentiated to obtain solitary differentiation data at a solitary differentiation point, the solitary differentiation data is filtered to obtain correction data for correcting a difference in signal level across a border between a rectangular block in which a block noise is generated and the adjacent block, and the correction data is added to the input video signal delayed by a predetermined time. Whereby, it is possible to get rid of a large difference across the border between blocks with the use of the correction data, and allow a block noise reducing apparatus to have a simple constitution.
(3) The technique disclosed in Patent Document 3 is aimed to high-accurately detect a block noise, which is prone to be generated in compressed video, from only pixel data without encoding information, and remove the block noise. For this purpose, a weighting process using features of a block noise is performed on spatial differences of video input signals, results of the weighting process are accumulated in the spatial direction to detect a block noise, and an additional cumulative process in a spatial direction, which is a different direction, is performed on results of the detection. Whereby, it is possible to avoid erroneous detection due to an effect of a random noise, which is prone to be generated when a block noise is detected, from only pixel data.
(4) The technique disclosed in Patent Document 4 is aimed to obtain a restored picture of high picture quality by effectively removing only noise components from compression-coded picture signals. For this purpose, restored picture signals are divided into predetermined unit blocks, whether or not the pixel level within a divided unit block is fluctuated is detected, a difference value between adjacent pixels in a unit block in which no fluctuation in level is detected and the adjacent block is determined, the difference value is compared with a predetermined threshold value to determine whether or not a block noise is generated, and a smoothing process is performed on adjacent unit blocks in which the difference value is less than the threshold value. Whereby, it is possible to avoid distortion of a displayed picture due to a block noise.
As shown in (1) of FIG. 25, for example, the techniques disclosed Patent Documents 1, 2 and 4, basically, obtain a difference (absolute value) between adjacent pixels within a frame as a difference across a pixel boundary for detecting a block noise, accumulate values (refer to reference numeral 101: detection signal=1) whose adjacent pixel difference absolute values are above a threshold value [“threshold value 1” in (1) of FIG. 25] in cycles of the block noise size as shown in (2) of FIG. 25 (in FIG. 25, the block noise size=8), and determine that a block noise is generated when the accumulated value of one frame is not less than a predetermined value [when not less than “threshold value 2” in (2) of FIG. 25] (refer to a portion enclosed by a broken line 102). Incidentally, the block noise size (block size) cycle is a cycle determined by a unit (a block size of 8×8 pixels, for example) in orthogonal transform process such as DCT transform or the like. A block noise size=8 signifies that 8×8 pixels are a unit block.
As shown in (1) of FIG. 26, the technique proposed in Patent Document 3 accumulates adjacent pixel difference absolute values which are not less than “threshold value 1” and not more than “threshold value 2” (refer to reference numeral 201: detection signal=1) in a frame in cycles of a block noise size (FIG. 26 shows an example where the block noise size=8), as shown in (2) of FIG. 26, and determines that a block noise is generated when the accumulated value of one frame is not less than a predetermined value (refer to a portion enclosed by a broken line 202).
As this, the known block noise detecting techniques obtain a difference (absolute value) between adjacent pixels as a basic amount used to detect a block noise, accumulate the values for one frame in the block noise cycles, and determine presence or absence of generation of a block noise on the basis of the magnitude of this accumulated value.
[Patent Document 1] Japanese Patent Application Laid-Open No. 2000-350202
[Patent Document 2] Japanese Patent Application Laid-Open No. 2001-119695
[Patent Document 3] Japanese Patent Application Laid-Open No. 2005-12641
[Patent Document 4] Japanese Patent Application Laid-Open No. HEI08-205157
However, there is a case where it is difficult to accurately detect a block noise from a difference value between adjacent pixels because it is usual that the difference value between the adjacent pixels is large in a portion where the picture (pixel) values are largely changed (the pixel boundary is inclined) although the block noise is not generated.
In addition, a value obtained by accumulating difference values between adjacent pixels in block noise cycles largely depends on contents of the picture, thus a value obtained by accumulating difference values between adjacent pixels in block size cycles is large in a complicated picture having a lot of high frequency components irrespective of presence or absence of generation of a block noise. This causes difficulty in finding accurately a block noise because it is difficult to discriminate between a case where a block noise is generated and a case where the picture is complicated.